Paracetamol extended release FDM 3D printlets: Evaluation of formulation variables on printability and drug release
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2021
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Paracetamol printlets were prepared via hot-melt extrusion process and fused deposition modelling, using two types of backbone polymers. Polycaprolactone (PCL) and Polyethylene oxides (PEO) 100 K and 200 K were used, while Arabic gum was used as a plasticizer to facilitate the material flow and Gelucire® 44/14 as an enhancer of drug release. Different drug/polymer ratios were prepared. Extrusion temperature was adjusted according to the mixture/polymer types. It was possible to produce filaments with maximum of 60% w/w of drug. Mechanical properties of filaments were evaluated using three-point bend test, while obtained parameters were modelled using decision tree as a data mining method. Correlation between maximum displacement, maximum force and printability was obtained with accuracy of 84.85% and can be a useful tool for predicting printability of filaments. This study briefly demonstrated that backbone polymer in formulation plays crucial role in obtaining FDM printlets with desir...ed properties. PEO-based filaments were more prone to be clogged in printcore, but their printlets showed much faster drug release. Drug release from all printlets was prolonged: from 50% in 8 h (PCL), to complete release in 4 h (PEO). Paracetamol release kinetics was guided by anomalous transport, attributed to the diffusion and erosion process.
Ključne reči:
3D printing / Decision tree model / Extended release / Fused deposition modelling / Printability / Three-point bend testIzvor:
International Journal of Pharmaceutics, 2021, 592Finansiranje / projekti:
DOI: 10.1016/j.ijpharm.2020.120053
ISSN: 0378-5173
WoS: 000600740100035
Scopus: 2-s2.0-85096158696
Institucija/grupa
PharmacyTY - JOUR AU - Đuranović, Marija AU - Obeid, Samiha AU - Madžarević, Marijana AU - Cvijić, Sandra AU - Ibrić, Svetlana PY - 2021 UR - https://farfar.pharmacy.bg.ac.rs/handle/123456789/3775 AB - Paracetamol printlets were prepared via hot-melt extrusion process and fused deposition modelling, using two types of backbone polymers. Polycaprolactone (PCL) and Polyethylene oxides (PEO) 100 K and 200 K were used, while Arabic gum was used as a plasticizer to facilitate the material flow and Gelucire® 44/14 as an enhancer of drug release. Different drug/polymer ratios were prepared. Extrusion temperature was adjusted according to the mixture/polymer types. It was possible to produce filaments with maximum of 60% w/w of drug. Mechanical properties of filaments were evaluated using three-point bend test, while obtained parameters were modelled using decision tree as a data mining method. Correlation between maximum displacement, maximum force and printability was obtained with accuracy of 84.85% and can be a useful tool for predicting printability of filaments. This study briefly demonstrated that backbone polymer in formulation plays crucial role in obtaining FDM printlets with desired properties. PEO-based filaments were more prone to be clogged in printcore, but their printlets showed much faster drug release. Drug release from all printlets was prolonged: from 50% in 8 h (PCL), to complete release in 4 h (PEO). Paracetamol release kinetics was guided by anomalous transport, attributed to the diffusion and erosion process. T2 - International Journal of Pharmaceutics T1 - Paracetamol extended release FDM 3D printlets: Evaluation of formulation variables on printability and drug release VL - 592 DO - 10.1016/j.ijpharm.2020.120053 ER -
@article{ author = "Đuranović, Marija and Obeid, Samiha and Madžarević, Marijana and Cvijić, Sandra and Ibrić, Svetlana", year = "2021", abstract = "Paracetamol printlets were prepared via hot-melt extrusion process and fused deposition modelling, using two types of backbone polymers. Polycaprolactone (PCL) and Polyethylene oxides (PEO) 100 K and 200 K were used, while Arabic gum was used as a plasticizer to facilitate the material flow and Gelucire® 44/14 as an enhancer of drug release. Different drug/polymer ratios were prepared. Extrusion temperature was adjusted according to the mixture/polymer types. It was possible to produce filaments with maximum of 60% w/w of drug. Mechanical properties of filaments were evaluated using three-point bend test, while obtained parameters were modelled using decision tree as a data mining method. Correlation between maximum displacement, maximum force and printability was obtained with accuracy of 84.85% and can be a useful tool for predicting printability of filaments. This study briefly demonstrated that backbone polymer in formulation plays crucial role in obtaining FDM printlets with desired properties. PEO-based filaments were more prone to be clogged in printcore, but their printlets showed much faster drug release. Drug release from all printlets was prolonged: from 50% in 8 h (PCL), to complete release in 4 h (PEO). Paracetamol release kinetics was guided by anomalous transport, attributed to the diffusion and erosion process.", journal = "International Journal of Pharmaceutics", title = "Paracetamol extended release FDM 3D printlets: Evaluation of formulation variables on printability and drug release", volume = "592", doi = "10.1016/j.ijpharm.2020.120053" }
Đuranović, M., Obeid, S., Madžarević, M., Cvijić, S.,& Ibrić, S.. (2021). Paracetamol extended release FDM 3D printlets: Evaluation of formulation variables on printability and drug release. in International Journal of Pharmaceutics, 592. https://doi.org/10.1016/j.ijpharm.2020.120053
Đuranović M, Obeid S, Madžarević M, Cvijić S, Ibrić S. Paracetamol extended release FDM 3D printlets: Evaluation of formulation variables on printability and drug release. in International Journal of Pharmaceutics. 2021;592. doi:10.1016/j.ijpharm.2020.120053 .
Đuranović, Marija, Obeid, Samiha, Madžarević, Marijana, Cvijić, Sandra, Ibrić, Svetlana, "Paracetamol extended release FDM 3D printlets: Evaluation of formulation variables on printability and drug release" in International Journal of Pharmaceutics, 592 (2021), https://doi.org/10.1016/j.ijpharm.2020.120053 . .